This overlay partitions Worker Groups by geographical location, data center, or data-sovereignty boundary to meet compliance needs and optimize network costs.

The core principle is to keep processing near the data, improving performance and simplifying compliance controls by aligning the physical placement of Worker Groups to data boundaries.

Common Regional Examples

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The primary use cases and examples of regional/geo patterns are:

• Regional Worker Groups (Spokes): Worker Groups placed per region (for example, wg-us-east, wg-eu-central) or data-sovereignty boundary. They handle initial ingest, local processing, and may forward a subset of curated data centrally.

• Central Core Worker Group (Optional): An optional, centralized Worker Group in a primary region that performs global aggregation, governance, or enrichment, receiving curated streams from the spokes.

• Cribl Edge Preference: Cribl Edge is preferred at remote sites for collection, local filtering, and buffering, sending data to the nearest Regional Worker Group to reduce bandwidth and improve resiliency.

Benefits

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• Compliance: Directly addresses legal and compliance requirements around data residency or sovereignty (such as GDPR), ensuring raw data does not cross defined boundaries.

• Cost control: Mitigates latency and egress cost concerns between regions by filtering, compressing, or summarizing data locally before sending it across expensive network links.

• Operational autonomy: Provides clear mapping from organizational or geographical boundaries to Worker Groups, simplifying access control, billing, and operational ownership for regional stakeholders.

Design Notes

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• Cribl Edge alignment: Ensure Edge Fleets are paired with their nearest Regional Worker Group to keep traffic local and maximize local buffering and filtering.

• Change management: Align each Regional Worker Group’s change cadence and risk profile to its local stakeholders, often independent of other regions.